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Could anyone help me on how to include offset parameter in NLMIXED model with negative binomial? Is the below inclusion of log_TotalWordsInSentence (log of number of words in a sentence) variable correct?
proc nlmixed data=myData;
xb = b0 + b1a*(Gender = 'female') + u;
mu = exp(xb + log_TotalWordsInSentence);
m = 1/alpha;
ll = lgamma(CountPronounsInSentence+m)-lgamma(CountPronounsInSentence+1)-lgamma(m)
+ CountPronounsInSentence*log(alpha*mu)-(CountPronounsInSentence+m)*log(1+alpha*mu);
model CountPronounsInSentence ~ general(ll);
random u ~ normal(0,s2u) subject=person_id;
run;
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sorry, i dont visit the message boards as frequently as i'd like to.... The code looks ok to me. Personally for clarity i might write it as:
bounds b2<=1, b2>=1;
xb = b0 + b1a*(Gender = 'female') + b2*log_TotalWordsInSentence + u;
mu = exp(xb);
and a minor thing: I'd reduce the length of the variable name 'CountPronounsInSentence' to make it readable, i didn't bother to read the loglikelihood equation ("ll = ")... because it's hard to read
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@pau13rown is probably a better person to answer this, but your formula looks okay to me. Alternatively, instead of
mu = exp(xb + log_TotalWordsInSentence);
you could use
mu = TotalWordsInSentence*(exp(xb));
which is equivalent (take log of both sides, bring log_TotalWordsInSentence to the left, combine logs, then exponentiate.)
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sorry, i dont visit the message boards as frequently as i'd like to.... The code looks ok to me. Personally for clarity i might write it as:
bounds b2<=1, b2>=1;
xb = b0 + b1a*(Gender = 'female') + b2*log_TotalWordsInSentence + u;
mu = exp(xb);
and a minor thing: I'd reduce the length of the variable name 'CountPronounsInSentence' to make it readable, i didn't bother to read the loglikelihood equation ("ll = ")... because it's hard to read
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